The present invention relates to computed tomography (CT) and, more particularly, to CT systems that reduce the effects of pseudo-enhancement, so air and soft tissues can be represented by their usual CT attenuations.
Colorectal cancer is one of the leading causes of cancer-related deaths. Patient screening can reduce colon cancer by facilitating early detection and removal of pre-cancerous polyps. Colonoscopy is considered to have the highest diagnostic performance for screening colon cancer; however, colonoscopy also has a high cost, risk of complications and incidents of patient non-compliance. A minimally invasive alternative procedure, called computed tomography colonography (CTC) or “virtual colonoscopy,” is expected to be more cost effective and to involve a lower risk of complications than traditional colonoscopy.
Proper bowel preparation is considered essential for confident detection of colorectal lesions using CTC. This preparation traditionally includes cathartic cleansing of a patient's colon, because residual material in the colon reduces the sensitivity of CTC by imitating polyps. However, cathartic cleansing usually involves administering a laxative. Such cleansings are uncomfortable for the patient, and some residual material remains in the colon, even after such a cleansing. Orally-administered radio-opaque (or high X-ray opacity) contrast agents, such as dilute barium, can be used to opacify residual fluid and stool, so these opacified (“tagged”) materials can be identified and distinguished from polyps or other soft tissues. Procedures that use such tagging are commonly referred to as “fecal tagging CTC” (ftCTC).
Interpreting a large number of ftCTC screening cases can be time-consuming for a radiologist, who may grow weary of the task and occasionally miss small polyps or even subtle cancers. Automated image processing (“computer-aided detection” (CAD)) tools can be used to rapidly point out suspicious lesions to radiologists. However, in ftCTC, automated image processing is complicated by an effect commonly known as pseudo-enhancement (PEH), which is an atrifactual increase in the observed X-ray opacity (radio density) of tissues due to the presence of a near-by high radio density tagging agent.
In computed tomography (CT), the internals of an object, such as a human body, are imaged by taking X-ray measurements, yielding data that represents the object as many tightly packed cubes (“voxels”). The radio density of each voxel is calculated by taking the X-ray measurements through the object from a large number of perspectives. A computer digitally processes the X-ray measurements and generates data that represents a three-dimensional model of the object, including the internals of the object. Essentially, the computer “stacks” a series of “slices” of the object to create the model. The data can then be analyzed by a CAD tool. Alternatively or in addition, the data can be used to generate a three-dimensional display or for some other purpose.
The radio density (also called the “CT attenuation” or “CT number”) of each voxel is represented by a numeric value along an arbitrary scale (the Hounsfield scale), in which −1,000 represents the radio density of air, and +1,000 represents the radio density of bone. Air causes very little X-ray attenuation and is typically depicted in black on X-ray films, in CT images, etc., whereas bone greatly attenuates X-rays and is typically depicted in white on these films and images. Fat has a radio density of about −120 Hounsfield Units (HU), and muscle has a radio density of about +40 HU. Water is defined as having a radio density of 0 (zero) HU.
Intermediate amounts of CT attenuation are usually depicted by shades of gray in CT images. Because the human eye is unable to distinguish among 2000 shades of grey (representing HU values between +1,000 and −1,000), a radiographer selects a range of CT attenuations that is of interest (i.e., a range of HU values, known as a “window”), and all the CT attenuations within this range are spread over an available gray scale, such as 256 shades of gray. This mapping of a range of CT attenuations to shades of gray is known as “windowing.” The center of the range is known as the “window level.” Materials having radio densities higher than the top of the window are depicted in white, whereas materials having radio densities lower than the bottom of the window are depicted in black.
Windowing facilitates distinguishing between tissues having similar radio densities. For example, to image an area of a body, such as the mediastinum or the abdomen, in which many tissues have similar radio densities, a narrow range of CT attenuations is selected, and these CT attenuations are spread over the available shades of gray. Consequently, two tissues with only a small difference between their radio densities are ascribed separate shades of gray and can, therefore, be differentiated.
Soft tissues, including polyps, typically have radio densities of less than 100 HU; however, a near-by tagging agent can pseudo-enhance the measured radio densities of these materials to more than 100 HU, sometimes as high as to 500 HU. Furthermore, the extent of this pseudo-enhancement can vary considerably within a single colon, in part because the amount, thickness and radio density of the tagging agent may vary from place to place within the colon.
This pseudo-enhancement degrades the performance of CAD tools, because these tools use fixed attenuation-based parameters. Thus, in pseudo-enhanced regions, some or all of the voxels that represent a polyp can be misclassified as tagged residual material, due to their high CT attenuations. Consequently, an automatically identified (“extracted”) region of the polyp can be significantly smaller than the actual region. In addition, the shape of the region can be severely distorted in the extraction, or the region can be missed entirely. Conventionally-calculated CT attenuation is not, therefore, a reliable feature for automated identification of tagged regions in ftCTC.